Cecil makes nature data consistent, accessible, and ready for analysis.
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Find nature datasets containing variables for your area of interest. Refine your search by spatial and temporal attributes across commercial and open licence datasets.
Join spatial data across multiple datasets. Use our recommended settings or configure reprojections to fit your preferred CRS and spatial resolution by default.
Securely connect your preferred languages and systems such as Python, R, GIS, and BI. Leverage SQL in your workflow to analyse time-series and spatial data at scale.
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Cecil draws on foundational scientific principles to identify and describe nature in an objective, transparent, and rigorous way.
We have developed a repeatable and scalable operating model with the research community to curate nature datasets and deliver the academic gold standard for nature data.
We collaborate with a network of industry experts to consolidate dataset protocols, methods, and specifications into clear and comprehensive documentation.
Cecil makes all datasets consistent and joinable by default. We consolidate nature datasets into relational database models, harmonise measurement units, and reproject pixel grids to a baseline CRS and spatial resolution using the appropriate resampling methods for continuous and categorical data.
We provide you with secure SQL access to a database optimised for time-series and spatial analysis at scale. This allows you to join large datasets from multiple data providers and perform complex aggregations and computations within milliseconds, delivering data insights with maximum efficiency.
Access curated nature datasets with one contract, one integration, and no minimum usage requirements. Cecil partners with leading data providers to streamline contracting, compliance, integrations, and technical support.
We currently support plant aboveground biomass, land use, and land cover datasets from industry leading data providers such as Chloris Geospatial, Kanop, and Planet Labs.
Get in touch to learn more about our roadmap. We would love to hear which datasets you would like us to prioritise.
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